Title :
Benefit evaluating of pumped storage station based on rough set and support vector machine
Author :
Sun, Wei ; Zhang, Xing
Author_Institution :
Dept. of Econ. Manage., North China Electr. Power Univ., Baoding
Abstract :
Based on the character and function of pumped storage station, a benefit evaluating indexes system is established.Considering the indexes are considerable, an hybrid model based on rough set (RS) and support vector machine(SVM) is proposed: Rough sets, as a anterior preprocessor of SVM, can find out the kernel factors influencing the safety of power supply enterprise by means of attribute reduction algorithm, and then, using them as the input vectors of SVM, the safety assessment is conducted. Experiment results compared with traditional SVM model show that the accuracy of the RS-SVM model are evidently improved .
Keywords :
power engineering computing; pumped-storage power stations; rough set theory; safety; support vector machines; attribute reduction; hybrid model; power supply enterprise; pumped storage station; rough set; safety assessment; support vector machine; Electrical safety; Electronic mail; Energy management; Intelligent control; Power system management; Pumps; Storage automation; Sun; Support vector machines; Virtual colonoscopy; attribute reduction algorithm; pumped storage station; rough set; support vector machine;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4593810